Python LMNN.set_diagonal Exemples

Exemple #1

Fichier : metagenomics_ape.py Projet : iglesias/tests

def diagonal_lmnn(features, labels, k=3, max_iter=10000):
    from modshogun import LMNN, MSG_DEBUG
    import numpy

    lmnn = LMNN(features, labels, k)
    # 	lmnn.io.set_loglevel(MSG_DEBUG)
    lmnn.set_diagonal(True)
    lmnn.set_maxiter(max_iter)
    lmnn.train(numpy.eye(features.get_num_features()))

    return lmnn

Exemple #2

Fichier : metagenomics_ape.py Projet : iglesias/tests

def diagonal_lmnn(features,labels,k=3,max_iter=10000):
	from modshogun import LMNN, MSG_DEBUG
	import numpy

	lmnn = LMNN(features,labels,k)
# 	lmnn.io.set_loglevel(MSG_DEBUG)
	lmnn.set_diagonal(True)
	lmnn.set_maxiter(max_iter)
	lmnn.train(numpy.eye(features.get_num_features()))

	return lmnn

Exemple #3

Fichier : multiclass_digits.py Projet : iglesias/tests

def lmnn_diagonal(train_features, train_labels, test_features, test_labels, k=1):
	from modshogun import LMNN, KNN, MSG_DEBUG, MulticlassAccuracy
	import numpy

	lmnn = LMNN(train_features, train_labels, k)
	lmnn.set_diagonal(True)
	lmnn.train()
	distance = lmnn.get_distance()

	knn = KNN(k, distance, train_labels) 
	knn.train()

	train_output = knn.apply()
	test_output = knn.apply(test_features)
	evaluator = MulticlassAccuracy()
	print 'LMNN-diagonal training error is %.4f' % ((1-evaluator.evaluate(train_output, train_labels))*100)
	print 'LMNN-diagonal test error is %.4f' % ((1-evaluator.evaluate(test_output, test_labels))*100)

Exemple #4

def lmnn_diagonal(train_features,
                  train_labels,
                  test_features,
                  test_labels,
                  k=1):
    from modshogun import LMNN, KNN, MSG_DEBUG, MulticlassAccuracy
    import numpy

    lmnn = LMNN(train_features, train_labels, k)
    lmnn.set_diagonal(True)
    lmnn.train()
    distance = lmnn.get_distance()

    knn = KNN(k, distance, train_labels)
    knn.train()

    train_output = knn.apply()
    test_output = knn.apply(test_features)
    evaluator = MulticlassAccuracy()
    print 'LMNN-diagonal training error is %.4f' % (
        (1 - evaluator.evaluate(train_output, train_labels)) * 100)
    print 'LMNN-diagonal test error is %.4f' % (
        (1 - evaluator.evaluate(test_output, test_labels)) * 100)

Exemple #5

Fichier : lmnn_metadistance_simdata.py Projet : iglesias/tests

#!/usr/bin/python

from scipy import io

data_dict = io.loadmat('../data/NBData20_train_preprocessed.mat')

xt = data_dict['xt']
yt = data_dict['yt']

import numpy
from modshogun import RealFeatures, MulticlassLabels, LMNN, MSG_DEBUG

features = RealFeatures(xt.T)
labels = MulticlassLabels(numpy.squeeze(yt))

k = 6
lmnn = LMNN(features, labels, k)
lmnn.io.set_loglevel(MSG_DEBUG)
lmnn.set_diagonal(True)
lmnn.set_maxiter(10000)
lmnn.train(numpy.eye(features.get_num_features()))

Exemple #6

Fichier : lmnn_metadistance_simdata.py Projet : iglesias/tests

#!/usr/bin/python

from scipy import io

data_dict = io.loadmat('../data/NBData20_train_preprocessed.mat')

xt = data_dict['xt']
yt = data_dict['yt']

import numpy
from modshogun import RealFeatures,MulticlassLabels,LMNN,MSG_DEBUG

features = RealFeatures(xt.T)
labels = MulticlassLabels(numpy.squeeze(yt))

k = 6
lmnn = LMNN(features,labels,k)
lmnn.io.set_loglevel(MSG_DEBUG)
lmnn.set_diagonal(True)
lmnn.set_maxiter(10000)
lmnn.train(numpy.eye(features.get_num_features()))